With the advancement in display technology, circuit design, and signal processing, it has become feasible to capture and render three dimensional (3D) videos on consumer platforms. A video is a sequence of scenes and a scene is a sequence of images called frames. Three dimensional videos have been recognized as one of the essential parts of next-generation visual media. Three dimensional videos may be represented using either stereo image recording (hereinafter may be referred to as ‘SIR’) or depth-image-based rendering (hereinafter may be referred to as ‘DIBR’). In SIR, left and right views for the same scene are captured simultaneously using different camera positions. Although the video is of a high quality, there are several drawbacks which limit its applicability in real-time applications. Firstly in SIR, both the cameras should have same parameters such as contrast, height, and brightness. It is very difficult and costly to set both the cameras with same parameters. DIBR, on the other hand, requires one center view and corresponding depth map. Virtual left and right views are generated by mapping the center view with its corresponding depth map to provide three dimensional experiences. In contrast to SIR, it offers several advantages. Firstly, depth degree is adjustable in the DIBR systems which help the viewers to adjust the depth condition they prefer. As the depth map is an 8-bit gray scale image, it requires less storage space and low transmission bandwidth. Further, center view video consists of color frames and can be used independently as two dimensional video i.e. DIBR systems have backward compatibility with the widely used two dimensional systems.
The convergence of networks, devices, and services combined with the technological advancements in digital storage, multimedia compression, and miniaturization of digital cameras has led to an explosive growth of online video content. In addition to the professionally produced video content, user-generated content and content produced by hardcore amateurs are also on the rise. Videos can easily be shared over the Internet using popular video sharing sites such as You Tube® and Yahoo!® Video. Three dimensional videos can be illegally distributed in multiple ways, including, but not limited to, unauthorized distribution of both the center video as well as depth video, unauthorized distribution of center video and unauthorized distribution of either left or right synthesized view. Although the user experience is enhanced with the new means of content production, distribution, and monetization, it has made illegal reproduction and distribution of digital content easier. Piracy of digital media content is increasing day by day and is a major cause of worry for the digital content owners. To protect the authenticity of three dimensional videos, a number of watermarking algorithms have been proposed. Watermarking is the process of embedding a watermark into an object such as a video which can be extracted later on from the suspected files for proving the digital rights.
To protect the copyright of three dimensional videos, few watermarking techniques have been proposed. Although a number of techniques exist for two dimensional watermarking, the mechanism to create and render two dimensional videos cannot be extrapolated to three dimensional videos since the nature of three dimensional videos differ from that of two dimensional videos. Three dimensional videos have depth-image-based rendering. DIBR videos have center view and depth map which are synthesized to generate left and right views to provide 3D experience. Koz et al. has proposed a watermarking scheme for the copyright protection of SIR three dimensional videos. The method is able to extract the watermark from known and unknown camera positions. Halici and Alatan have proposed a watermarking method for DIBR images. A watermark is embedded in spatial domain with a weighting factor. The method may not be robust against non-linear transformations such as rotation. Algorithms such as Singular Value Decomposition (hereinafter may be referred to as ‘SVD’) have gained importance due to its robustness to withstand attacks relative to algorithms such as Discrete Cosine Transform (hereinafter may be referred to as ‘DCT’) and Discrete Wavelet Transform (hereinafter may be referred to as ‘DWT’). Various methods have been proposed to watermark digital images using SVD. However, the application of SVD in watermarking of videos is difficult. This limitation exists primarily due to temporal nature of videos, presence of special effects in videos, and non-blind nature of SVD based methods.